In order to address the issue mentioned above, various methods have been reported in the literature. Some methods voxelize the 3D points to employ the 3D discrete convolution [1]}, [2]}. However, it increases the computational complexity and the memory requirement for processing the 3D points. Prior works like sparse convolutional neural networks can also be employed, but they operate only on nonempty voxels [3]}. Further, some of the approaches directly operate on 3D points and extract information via soft max-pooling layers [4]}, [5]}, [6]}. Another family of methods combines the information in the form of 3D points set into a graph for directive passing [7]}, [8]}.
